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   "source": [
    "# Assignment 1: Bandits and Exploration/Exploitation"
   ]
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    "Welcome to Assignment 1. This notebook will:\n",
    "- Help you create your first bandit algorithm\n",
    "- Help you understand the effect of epsilon on exploration and learn about the exploration/exploitation tradeoff\n",
    "- Introduce you to some of the reinforcement learning software we are going to use for this specialization\n",
    "\n",
    "This class uses RL-Glue to implement most of our experiments. It was originally designed by Adam White, Brian Tanner, and Rich Sutton. This library will give you a solid framework to understand how reinforcement learning experiments work and how to run your own. If it feels a little confusing at first, don't worry - we are going to walk you through it slowly and introduce you to more and more parts as you progress through the specialization.\n",
    "\n",
    "We are assuming that you have used a Jupyter notebook before. But if not, it is quite simple. Simply press the run button, or shift+enter to run each of the cells. The places in the code that you need to fill in will be clearly marked for you."
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   "source": [
    "## Section 0: Preliminaries"
   ]
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    "# Import necessary libraries\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from rl_glue import RLGlue\n",
    "import main_agent\n",
    "import ten_arm_env\n",
    "import test_env\n",
    "from tqdm import tqdm\n",
    "import time"
   ]
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    "In the above cell, we import the libraries we need for this assignment. We use numpy throughout the course and occasionally provide hints for which methods to use in numpy. Other than that we mostly use vanilla python and the occasional other library, such as matplotlib for making plots.\n",
    "\n",
    "You might have noticed that we import ten_arm_env. This is the __10-armed Testbed__ introduced in [section 2.3](http://www.incompleteideas.net/book/RLbook2018.pdf) of the textbook. We use this throughout this notebook to test our bandit agents. It has 10 arms, which are the actions the agent can take. Pulling an arm generates a stochastic reward from a Gaussian distribution with unit-variance. For each action, the expected value of that action is randomly sampled from a normal distribution, at the start of each run. If you are unfamiliar with the 10-armed Testbed please review it in the textbook before continuing.\n",
    "\n",
    "DO NOT IMPORT OTHER LIBRARIES as this will break the autograder."
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   "source": [
    "## Section 1: Greedy Agent"
   ]
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    "We want to create an agent that will find the action with the highest expected reward. One way an agent could operate is to always choose the action with  the highest value based on the agent’s current estimates. This is called a greedy agent as it greedily chooses the action that it thinks has the highest value. Let's look at what happens in this case.\n",
    "\n",
    "First we are going to implement the argmax function, which takes in a list of action values and returns an action with the highest value. Why are we implementing our own instead of using the argmax function that numpy uses? Numpy's argmax function returns the first instance of the highest value. We do not want that to happen as it biases the agent to choose a specific action in the case of ties. Instead we want to break ties between the highest values randomly. So we are going to implement our own argmax function. You may want to look at [np.random.choice](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.choice.html) to randomly select from a list of values."
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    "# [Graded]\n",
    "def argmax(q_values):\n",
    "    \"\"\"\n",
    "    Takes in a list of q_values and returns the index\n",
    "    of the item with the highest value. Breaks ties randomly.\n",
    "    returns: int - the index of the highest value in q_values\n",
    "    \"\"\"\n",
    "    top = float(\"-inf\")\n",
    "    ties = []\n",
    "    \n",
    "    for i in range(len(q_values)):\n",
    "        # if a value in q_values is greater than the highest value, then update top and reset ties to zero\n",
    "        # if a value is equal to top value, then add the index to ties (hint: do this no matter what)\n",
    "        # return a random selection from ties. (hint: look at np.random.choice)\n",
    "        ### START CODE HERE ###\n",
    "        if q_values[i] > top:\n",
    "            top = q_values[i]\n",
    "            ties.clear()\n",
    "#             ties.append(i)\n",
    "            \n",
    "        if q_values[i] == top:\n",
    "            ties.append(i)\n",
    "            \n",
    "    ans = np.random.choice(ties)\n",
    "    \n",
    "        \n",
    "        ### END CODE HERE ###\n",
    "    return ans # change this"
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   "source": [
    "# Test argmax implentation\n",
    "test_array = [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]\n",
    "assert argmax(test_array) == 8, \"Check your argmax implementation returns the index of the largest value\"\n",
    "\n",
    "test_array = [1, 0, 0, 1]\n",
    "total = 0\n",
    "for i in range(100):\n",
    "    total += argmax(test_array)\n",
    "\n",
    "assert total > 0, \"Make sure your argmax implementation randomly choooses among the largest values.\"\n",
    "assert total != 300, \"Make sure your argmax implementation randomly choooses among the largest values.\""
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    "# Do not modify this cell\n",
    "# Test for Argmax Function\n",
    "def test_argmax(): \n",
    "    test_array = [1, 0, 0, 1]\n",
    "    total = 0\n",
    "    for i in range(100):\n",
    "        total += argmax(test_array)\n",
    "    np.save(\"argmax_test\", total)\n",
    "    return total\n",
    "test_argmax()"
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   "source": [
    "Now we introduce the first part of an RL-Glue agent that you will implement. Here we are going to create a GreedyAgent and implement the agent_step method. This method gets called each time the agent takes a step. The method has to return the action selected by the agent. This method also ensures the agent’s estimates are updated based on the signals it gets from the environment.\n",
    "\n",
    "Fill in the code below to implement a greedy agent."
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   "source": [
    "# Greedy agent here [Graded]\n",
    "class GreedyAgent(main_agent.Agent):\n",
    "    def agent_step(self, reward, observation):\n",
    "        \"\"\"\n",
    "        Takes one step for the agent. It takes in a reward and observation and \n",
    "        returns the action the agent chooses at that time step.\n",
    "        \n",
    "        Arguments:\n",
    "        reward -- float, the reward the agent received from the environment after taking the last action.\n",
    "        observation -- float, the observed state the agent is in. Do not worry about this for this assignment \n",
    "        as you will not use it until future lessons.\n",
    "        Returns:\n",
    "        current_action -- int, the action chosen by the agent at the current time step.\n",
    "        \"\"\"\n",
    "        ### Useful Class Variables ###\n",
    "        # self.q_values : An array with the agent’s value estimates for each action.\n",
    "        # self.arm_count : An array with a count of the number of times each arm has been pulled.\n",
    "        # self.last_action : The action that the agent took on the previous time step.\n",
    "        #######################\n",
    "        \n",
    "        # current action = ? # Use the argmax function you created above\n",
    "        # (~2 lines)\n",
    "        ### START CODE HERE ###\n",
    "        \n",
    "        self.last_action = int(self.last_action)\n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        # Update action values. Hint: Look at the algorithm in section 2.4 of the textbook.\n",
    "        # Increment the counter in self.arm_count for the action from the previous time step\n",
    "        # Update the step size using self.arm_count\n",
    "        # Update self.q_values for the action from the previous time step\n",
    "        # (~3-5 lines)\n",
    "        ### START CODE HERE ###\n",
    "        self.arm_count[self.last_action] += 1\n",
    "        step_size = 1/self.arm_count[self.last_action]\n",
    "        self.q_values[self.last_action] = self.q_values[self.last_action]+ step_size*(reward - self.q_values[self.last_action])\n",
    "        \n",
    "        current_action = argmax(self.q_values)\n",
    "        ### END CODE HERE ###\n",
    "    \n",
    "        self.last_action = current_action\n",
    "        \n",
    "        return current_action\n",
    "        "
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     "text": [
      "Output:\n",
      "[0, 0.5, 1.0, 0, 0]\n",
      "Expected Output:\n",
      "[0, 0.5, 1.0, 0, 0]\n"
     ]
    }
   ],
   "source": [
    "# Do not modify this cell\n",
    "# Test for Greedy Agent Code\n",
    "greedy_agent = GreedyAgent()\n",
    "greedy_agent.q_values = [0, 0, 1.0, 0, 0]\n",
    "greedy_agent.arm_count = [0, 1, 0, 0, 0]\n",
    "greedy_agent.last_action = 1\n",
    "action = greedy_agent.agent_step(1, 0)\n",
    "np.save(\"greedy_test\", greedy_agent.q_values)\n",
    "print(\"Output:\")\n",
    "print(greedy_agent.q_values)\n",
    "print(\"Expected Output:\")\n",
    "print([0, 0.5, 1.0, 0, 0])\n",
    "\n",
    "assert action == 2, \"Check that you are using argmax to choose the action with the highest value.\"\n",
    "assert greedy_agent.q_values == [0, 0.5, 1.0, 0, 0], \"Check that you are updating q_values correctly.\""
   ]
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   "source": [
    "Let's visualize the result. Here we run an experiment using RL-Glue to test our agent. For now, we will set up the experiment code; in future lessons, we will walk you through running experiments so that you can create your own."
   ]
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     "text": [
      "100%|██████████| 200/200 [00:09<00:00, 20.48it/s]\n"
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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Greedy Result\n",
    "num_runs = 200                    # The number of times we run the experiment\n",
    "num_steps = 1000                  # The number of steps each experiment is run for\n",
    "env = ten_arm_env.Environment     # We the environment to use\n",
    "agent = GreedyAgent               # We choose what agent we want to use\n",
    "agent_info = {\"num_actions\": 10}  # Pass the agent the information it needs; \n",
    "                                  # here it just needs the number of actions (number of arms).\n",
    "env_info = {}                     # Pass the environment the information it needs; in this case, it is nothing.\n",
    "\n",
    "all_averages = []\n",
    "\n",
    "for i in tqdm(range(num_runs)):           # tqdm is what creates the progress bar below once the code is run\n",
    "    rl_glue = RLGlue(env, agent)          # Creates a new RLGlue experiment with the env and agent we chose above\n",
    "    rl_glue.rl_init(agent_info, env_info) # Pass RLGlue what it needs to initialize the agent and environment\n",
    "    rl_glue.rl_start()                    # Start the experiment\n",
    "\n",
    "    scores = [0]\n",
    "    averages = []\n",
    "    \n",
    "    for i in range(num_steps):\n",
    "        reward, _, action, _ = rl_glue.rl_step() # The environment and agent take a step and return\n",
    "                                                 # the reward, and action taken.\n",
    "        scores.append(scores[-1] + reward)\n",
    "        averages.append(scores[-1] / (i + 1))\n",
    "    all_averages.append(averages)\n",
    "\n",
    "plt.figure(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "plt.plot([1.55 for _ in range(num_steps)], linestyle=\"--\")\n",
    "plt.plot(np.mean(all_averages, axis=0))\n",
    "plt.legend([\"Best Possible\", \"Greedy\"])\n",
    "plt.title(\"Average Reward of Greedy Agent\")\n",
    "plt.xlabel(\"Steps\")\n",
    "plt.ylabel(\"Average reward\")\n",
    "plt.show()\n",
    "greedy_scores = np.mean(all_averages, axis=0)\n",
    "np.save(\"greedy_scores\", greedy_scores)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "a853027b4891a856372c381b05461a4f",
     "grade": false,
     "grade_id": "cell-04a8bd103b7af798",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "How did our agent do? Is it possible for it to do better?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 2: Epsilon-Greedy Agent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We learned about [another way for an agent to operate](https://www.coursera.org/learn/fundamentals-of-reinforcement-learning/lecture/tHDck/what-is-the-trade-off), where it does not always take the greedy action. Instead, sometimes it takes an exploratory action. It does this so that it can find out what the best action really is. If we always choose what we think is the current best action is, we may miss out on taking the true best action, because we haven't explored enough times to find that best action.\n",
    "\n",
    "Implement an epsilon-greedy agent below. Hint: we are implementing the algorithm from [section 2.4](http://www.incompleteideas.net/book/RLbook2018.pdf#page=52) of the textbook. You may want to use your greedy code from above and look at [np.random.random](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.random.html), as well as [np.random.randint](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.randint.html), to help you select random actions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "checksum": "429854284bed39ce9541cd58ebd13067",
     "grade": false,
     "grade_id": "cell-6862cb5ef5702d22",
     "locked": false,
     "schema_version": 1,
     "solution": true
    }
   },
   "outputs": [],
   "source": [
    "# Epsilon Greedy Agent here [Graded]\n",
    "class EpsilonGreedyAgent(main_agent.Agent):\n",
    "    def agent_step(self, reward, observation):\n",
    "        \"\"\"\n",
    "        Takes one step for the agent. It takes in a reward and observation and \n",
    "        returns the action the agent chooses at that time step.\n",
    "        \n",
    "        Arguments:\n",
    "        reward -- float, the reward the agent received from the environment after taking the last action.\n",
    "        observation -- float, the observed state the agent is in. Do not worry about this for this assignment \n",
    "        as you will not use it until future lessons.\n",
    "        Returns:\n",
    "        current_action -- int, the action chosen by the agent at the current time step.\n",
    "        \"\"\"\n",
    "        \n",
    "        ### Useful Class Variables ###\n",
    "        # self.q_values : An array with the agent’s value estimates for each action.\n",
    "        # self.arm_count : An array with a count of the number of times each arm has been pulled.\n",
    "        # self.last_action : The action that the agent took on the previous time step.\n",
    "        # self.epsilon : The probability an epsilon greedy agent will explore (ranges between 0 and 1)\n",
    "        #######################\n",
    "        \n",
    "        # Choose action using epsilon greedy\n",
    "        # Randomly choose a number between 0 and 1 and see if it is less than self.epsilon\n",
    "        # (Hint: look at np.random.random()). If it is, set current_action to a random action.\n",
    "        # Otherwise choose current_action greedily as you did above.\n",
    "        # (~4 lines)\n",
    "        ### START CODE HERE ###\n",
    "        last_action = int(self.last_action)\n",
    "        \n",
    "        \n",
    "        \n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        # Update action-values - this should be the same update as your greedy agent above\n",
    "        # (~3-5 lines)\n",
    "        ### START CODE HERE ###\n",
    "        self.arm_count[last_action] += 1\n",
    "        step_size = 1/self.arm_count[last_action]\n",
    "        self.q_values[last_action] += step_size*(reward - self.q_values[last_action])\n",
    "        \n",
    "        # find current\n",
    "        thre = np.random.random()\n",
    "        if thre < self.epsilon:\n",
    "            current_action = np.random.randint(self.num_actions)\n",
    "        else:\n",
    "            current_action = argmax(self.q_values)\n",
    "        \n",
    "        \n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        self.last_action = current_action\n",
    "        \n",
    "        return current_action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "e530a16b139b2a9966b1a65e25086f70",
     "grade": true,
     "grade_id": "cell-3099aff70dfd2e61",
     "locked": true,
     "points": 0,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output:\n",
      "[0, 0.5, 1.0, 0, 0]\n",
      "Expected Output:\n",
      "[0, 0.5, 1.0, 0, 0]\n"
     ]
    }
   ],
   "source": [
    "# Do not modify this cell\n",
    "# Test Code for Epsilon Greedy Agent\n",
    "e_greedy_agent = EpsilonGreedyAgent()\n",
    "e_greedy_agent.q_values = [0, 0, 1.0, 0, 0]\n",
    "e_greedy_agent.arm_count = [0, 1, 0, 0, 0]\n",
    "e_greedy_agent.num_actions = 5\n",
    "e_greedy_agent.last_action = 1\n",
    "e_greedy_agent.epsilon = 0.5\n",
    "action = e_greedy_agent.agent_step(1, 0)\n",
    "print(\"Output:\")\n",
    "print(e_greedy_agent.q_values)\n",
    "print(\"Expected Output:\")\n",
    "print([0, 0.5, 1.0, 0, 0])\n",
    "\n",
    "# assert action == 2, \"Check that you are using argmax to choose the action with the highest value.\"\n",
    "assert e_greedy_agent.q_values == [0, 0.5, 1.0, 0, 0], \"Check that you are updating q_values correctly.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "5488f20b68110a856dad3a003f51db32",
     "grade": false,
     "grade_id": "cell-762b0b3997c2300f",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Now that we have our epsilon greedy agent created. Let's compare it against the greedy agent with epsilon of 0.1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "9a2b47a106185d21f2e00f81871f7476",
     "grade": false,
     "grade_id": "cell-2f6cef9d3ecdace7",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 200/200 [00:07<00:00, 26.31it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Epsilon greedy results and greedy results\n",
    "num_runs = 200\n",
    "num_steps = 1000\n",
    "epsilon = 0.1\n",
    "agent = EpsilonGreedyAgent\n",
    "env = ten_arm_env.Environment\n",
    "agent_info = {\"num_actions\": 10, \"epsilon\": epsilon}\n",
    "env_info = {}\n",
    "all_averages = []\n",
    "\n",
    "for i in tqdm(range(num_runs)):\n",
    "    rl_glue = RLGlue(env, agent)\n",
    "    rl_glue.rl_init(agent_info, env_info)\n",
    "    rl_glue.rl_start()\n",
    "\n",
    "    scores = [0]\n",
    "    averages = []\n",
    "    for i in range(num_steps):\n",
    "        reward, _, action, _ = rl_glue.rl_step() # The environment and agent take a step and return\n",
    "                                                 # the reward, and action taken.\n",
    "        scores.append(scores[-1] + reward)\n",
    "        averages.append(scores[-1] / (i + 1))\n",
    "    all_averages.append(averages)\n",
    "\n",
    "plt.figure(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "plt.plot([1.55 for _ in range(num_steps)], linestyle=\"--\")\n",
    "plt.plot(greedy_scores)\n",
    "plt.title(\"Average Reward of Greedy Agent vs. Epsilon-Greedy Agent\")\n",
    "plt.plot(np.mean(all_averages, axis=0))\n",
    "plt.legend((\"Best Possible\", \"Greedy\", \"Epsilon Greedy: Epsilon = 0.1\"))\n",
    "plt.xlabel(\"Steps\")\n",
    "plt.ylabel(\"Average reward\")\n",
    "plt.show()\n",
    "np.save(\"e-greedy\", all_averages)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "ed0fa5039cf69237a1caf29b273b2942",
     "grade": false,
     "grade_id": "cell-23cf04f952075345",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Notice how much better the epsilon-greedy agent did. Because we occasionally choose a random action we were able to find a better long term policy. By acting greedily before our value estimates are accurate, we risk settling on a suboptimal action."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "7acf4c8b67b66a59bd737bbb29d3d9f7",
     "grade": false,
     "grade_id": "cell-edb9184608392c62",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "## 1.2 Averaging Multiple Runs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "7c51be606d9d6554fdd916078b0bda57",
     "grade": false,
     "grade_id": "cell-1b55f263f08b1389",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Did you notice that we averaged over 2000 runs? Why did we do that?\n",
    "\n",
    "To get some insight, let's look at the results of two individual runs by the same agent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "6a98c68aa5e4e1270799ea04bed4721f",
     "grade": false,
     "grade_id": "cell-69d62e83fc1d91bc",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot runs of e-greedy agent\n",
    "agent = EpsilonGreedyAgent\n",
    "agent_info = {\"num_actions\": 10, \"epsilon\": 0.1}\n",
    "env_info = {}\n",
    "all_averages = []\n",
    "plt.figure(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "num_steps = 1000\n",
    "\n",
    "for run in (0, 1):\n",
    "    np.random.seed(run) # Here we set the seed so that we can compare two different runs\n",
    "    averages = []\n",
    "    rl_glue = RLGlue(env, agent)\n",
    "    rl_glue.rl_init(agent_info, env_info)\n",
    "    rl_glue.rl_start()\n",
    "\n",
    "    scores = [0]\n",
    "    for i in range(num_steps):\n",
    "        reward, state, action, is_terminal = rl_glue.rl_step()\n",
    "        scores.append(scores[-1] + reward)\n",
    "        averages.append(scores[-1] / (i + 1))\n",
    "#     all_averages.append(averages)\n",
    "    plt.plot(averages)\n",
    "\n",
    "# plt.plot(greedy_scores)\n",
    "plt.title(\"Comparing two runs of the same agent\")\n",
    "plt.xlabel(\"Steps\")\n",
    "plt.ylabel(\"Average reward\")\n",
    "# plt.plot(np.mean(all_averages, axis=0))\n",
    "# plt.legend((\"Greedy\", \"Epsilon: 0.1\"))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "9c6b5d4ea841a388245eb1fdc732a3ed",
     "grade": false,
     "grade_id": "cell-cbabc6468847faab",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Notice how the two runs were different? But, if this is the exact same algorithm, why does it behave differently in these two runs?\n",
    "\n",
    "The answer is that it is due to randomness in the environment and in the agent. Depending on what action the agent randomly starts with, or when it randomly chooses to explore, it can change the results of the runs. And even if the agent chooses the same action, the reward from the environment is randomly sampled from a Gaussian. The agent could get lucky, and see larger rewards for the best action early on and so settle on the best action faster. Or, it could get unlucky and see smaller rewards for best action early on and so take longer to recognize that it is in fact the best action.\n",
    "\n",
    "To be more concrete, let’s look at how many times an exploratory action is taken, for different seeds. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "9c0105d5ee8f26ec966704dad4d013f0",
     "grade": false,
     "grade_id": "cell-a6e9ef699d799240",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Seed 1\n",
      "Exploratory Action\n",
      "Exploratory Action\n",
      "Exploratory Action\n",
      "\n",
      "\n",
      "Random Seed 2\n",
      "Exploratory Action\n"
     ]
    }
   ],
   "source": [
    "print(\"Random Seed 1\")\n",
    "np.random.seed(1)\n",
    "for _ in range(15):\n",
    "    if np.random.random() < 0.1:\n",
    "        print(\"Exploratory Action\")\n",
    "    \n",
    "\n",
    "print()\n",
    "print()\n",
    "\n",
    "print(\"Random Seed 2\")\n",
    "np.random.seed(2)\n",
    "for _ in range(15):\n",
    "    if np.random.random() < 0.1:\n",
    "        print(\"Exploratory Action\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "bc8ff22ac82750f9eb3e0f901d5f4166",
     "grade": false,
     "grade_id": "cell-42f5c9cb11fffbb0",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "With the first seed, we take an exploratory action three times out of 15, but with the second, we only take an exploratory action once. This can significantly affect the performance of our agent because the amount of exploration has changed significantly.\n",
    "\n",
    "To compare algorithms, we therefore report performance averaged across many runs. We do this to ensure that we are not simply reporting a result that is due to stochasticity, as explained [in the lectures](https://www.coursera.org/learn/fundamentals-of-reinforcement-learning/lecture/PtVBs/sequential-decision-making-with-evaluative-feedback). Rather, we want statistically significant outcomes. We will not use statistical significance tests in this course. Instead, because we have access to simulators for our experiments, we use the simpler strategy of running for a large number of runs and ensuring that the confidence intervals do not overlap. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "65cc408096713cec77d263be0fd90b0d",
     "grade": false,
     "grade_id": "cell-1d4132f4b28f4881",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "## Section 3: Comparing values of epsilon"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "81b41ca2616b4d370e19c911cf4ab88e",
     "grade": false,
     "grade_id": "cell-f62fa977aac5da68",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Can we do better than an epsilon of 0.1? Let's try several different values for epsilon and see how they perform. We try different settings of key performance parameters to understand how the agent might perform under different conditions.\n",
    "\n",
    "Below we run an experiment where we sweep over different values for epsilon:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "2d9ab9563f8699e0b8aabcb1087f454b",
     "grade": false,
     "grade_id": "cell-4c9881740ba46656",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 200/200 [00:08<00:00, 23.84it/s]\n",
      "100%|██████████| 200/200 [00:08<00:00, 24.31it/s]\n",
      "100%|██████████| 200/200 [00:07<00:00, 26.70it/s]\n",
      "100%|██████████| 200/200 [00:05<00:00, 38.41it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Experiment code for epsilon-greedy with different values of epsilon\n",
    "epsilons = [0.0, 0.01, 0.1, 0.4]\n",
    "\n",
    "plt.figure(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "plt.plot([1.55 for _ in range(num_steps)], linestyle=\"--\")\n",
    "\n",
    "n_q_values = []\n",
    "n_averages = []\n",
    "n_best_actions = []\n",
    "\n",
    "num_runs = 200\n",
    "\n",
    "for epsilon in epsilons:\n",
    "    all_averages = []\n",
    "    for run in tqdm(range(num_runs)):\n",
    "        agent = EpsilonGreedyAgent\n",
    "        agent_info = {\"num_actions\": 10, \"epsilon\": epsilon}\n",
    "        env_info = {\"random_seed\": run}\n",
    "\n",
    "        rl_glue = RLGlue(env, agent)\n",
    "        rl_glue.rl_init(agent_info, env_info)\n",
    "        rl_glue.rl_start()\n",
    "        \n",
    "        best_arm = np.argmax(rl_glue.environment.arms)\n",
    "\n",
    "        scores = [0]\n",
    "        averages = []\n",
    "        best_action_chosen = []\n",
    "        \n",
    "        for i in range(num_steps):\n",
    "            reward, state, action, is_terminal = rl_glue.rl_step()\n",
    "            scores.append(scores[-1] + reward)\n",
    "            averages.append(scores[-1] / (i + 1))\n",
    "            if action == best_arm:\n",
    "                best_action_chosen.append(1)\n",
    "            else:\n",
    "                best_action_chosen.append(0)\n",
    "            if epsilon == 0.1 and run == 0:\n",
    "                n_q_values.append(np.copy(rl_glue.agent.q_values))\n",
    "        if epsilon == 0.1:\n",
    "            n_averages.append(averages)\n",
    "            n_best_actions.append(best_action_chosen)\n",
    "        all_averages.append(averages)\n",
    "        \n",
    "    plt.plot(np.mean(all_averages, axis=0))\n",
    "plt.legend([\"Best Possible\"] + epsilons)\n",
    "plt.xlabel(\"Steps\")\n",
    "plt.ylabel(\"Average reward\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "621e4edf3ee0456e562f8f61899fafd8",
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   "source": [
    "Why did 0.1 perform better than 0.01?\n",
    "\n",
    "If exploration helps why did 0.4 perform worse that 0.0 (the greedy agent)?\n",
    "\n",
    "Think about these and how you would answer these questions. They are questions in the practice quiz. If you still have questions about it, retake the practice quiz."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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    "nbgrader": {
     "checksum": "4107b76e0b504556e7760f38c7c603b2",
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     "schema_version": 1,
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    }
   },
   "source": [
    "## Section 4: The Effect of Step Size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
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   "source": [
    "In Section 1 of this assignment, we decayed the step size over time based on action-selection counts. The step-size was 1/N(A), where N(A) is the number of times action A was selected. This is the same as computing a sample average. We could also set the step size to be a constant value, such as 0.1. What would be the effect of doing that? And is it better to use a constant or the sample average method? \n",
    "\n",
    "To investigate this question, let’s start by creating a new agent that has a constant step size. This will be nearly identical to the agent created above. You will use the same code to select the epsilon-greedy action. You will change the update to have a constant step size instead of using the 1/N(A) update."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "deletable": false,
    "nbgrader": {
     "checksum": "47980d497fbd713522992e77769f9fad",
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     "grade_id": "cell-fe26903228ef0c50",
     "locked": false,
     "schema_version": 1,
     "solution": true
    }
   },
   "outputs": [],
   "source": [
    "# Constant Step Size Agent Here [Graded]\n",
    "# Greedy agent here\n",
    "class EpsilonGreedyAgentConstantStepsize(main_agent.Agent):\n",
    "    def agent_step(self, reward, observation):\n",
    "        \"\"\"\n",
    "        Takes one step for the agent. It takes in a reward and observation and \n",
    "        returns the action the agent chooses at that time step.\n",
    "        \n",
    "        Arguments:\n",
    "        reward -- float, the reward the agent received from the environment after taking the last action.\n",
    "        observation -- float, the observed state the agent is in. Do not worry about this for this assignment \n",
    "        as you will not use it until future lessons.\n",
    "        Returns:\n",
    "        current_action -- int, the action chosen by the agent at the current time step.\n",
    "        \"\"\"\n",
    "        \n",
    "        ### Useful Class Variables ###\n",
    "        # self.q_values : An array with the agent’s value estimates for each action.\n",
    "        # self.arm_count : An array with a count of the number of times each arm has been pulled.\n",
    "        # self.last_action : The action that the agent took on the previous time step.\n",
    "        # self.step_size : A float which is the current step size for the agent.\n",
    "        # self.epsilon : The probability an epsilon greedy agent will explore (ranges between 0 and 1)\n",
    "        #######################\n",
    "        \n",
    "        # Choose action using epsilon greedy. This is the same as you implemented above.\n",
    "        # (~4 lines)\n",
    "        ### START CODE HERE ###\n",
    "        last_action = int(self.last_action)\n",
    "        \n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        # Update q_values for action taken at previous time step \n",
    "        # using self.step_size intead of using self.arm_count\n",
    "        # (~1-2 lines)\n",
    "        ### START CODE HERE ###\n",
    "#         self.arm_count[last_action] += 1\n",
    "        self.q_values[last_action] += self.step_size*(reward - self.q_values[last_action])\n",
    "        \n",
    "        \n",
    "        thre = np.random.random()\n",
    "        if thre < self.epsilon:\n",
    "            current_action = np.random.randint(self.num_actions)\n",
    "        else:\n",
    "            current_action = argmax(self.q_values)\n",
    "        \n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        self.last_action = current_action\n",
    "        \n",
    "        return current_action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "fb2ba0590f0266b9aac4956d8f3c5489",
     "grade": true,
     "grade_id": "cell-ba6bdf28928e3042",
     "locked": true,
     "points": 0,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output for step size: 0.01\n",
      "[0, 0.01, 1.0, 0, 0]\n",
      "Expected Output:\n",
      "[0, 0.01, 1.0, 0, 0]\n",
      "Output for step size: 0.1\n",
      "[0, 0.1, 1.0, 0, 0]\n",
      "Expected Output:\n",
      "[0, 0.1, 1.0, 0, 0]\n",
      "Output for step size: 0.5\n",
      "[0, 0.5, 1.0, 0, 0]\n",
      "Expected Output:\n",
      "[0, 0.5, 1.0, 0, 0]\n",
      "Output for step size: 1.0\n",
      "[0, 1.0, 1.0, 0, 0]\n",
      "Expected Output:\n",
      "[0, 1.0, 1.0, 0, 0]\n"
     ]
    }
   ],
   "source": [
    "# Do not modify this cell\n",
    "# Test Code for Epsilon Greedy with Different Constant Stepsizes\n",
    "for step_size in [0.01, 0.1, 0.5, 1.0]:\n",
    "    e_greedy_agent = EpsilonGreedyAgentConstantStepsize()\n",
    "    e_greedy_agent.q_values = [0, 0, 1.0, 0, 0]\n",
    "    # e_greedy_agent.arm_count = [0, 1, 0, 0, 0]\n",
    "    e_greedy_agent.num_actions = 5\n",
    "    e_greedy_agent.last_action = 1\n",
    "    e_greedy_agent.epsilon = 0.0\n",
    "    e_greedy_agent.step_size = step_size\n",
    "    action = e_greedy_agent.agent_step(1, 0)\n",
    "    print(\"Output for step size: {}\".format(step_size))\n",
    "    print(e_greedy_agent.q_values)\n",
    "    print(\"Expected Output:\")\n",
    "    print([0, step_size, 1.0, 0, 0])\n",
    "    assert e_greedy_agent.q_values == [0, step_size, 1.0, 0, 0], \"Check that you are updating q_values correctly using the stepsize.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "005b2c64dcbef3a81bee85d79af688a4",
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     "grade_id": "cell-a5d327f4d52578e6",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 200/200 [00:07<00:00, 26.16it/s]\n",
      "100%|██████████| 200/200 [00:07<00:00, 25.55it/s]\n",
      "100%|██████████| 200/200 [00:07<00:00, 27.41it/s]\n",
      "100%|██████████| 200/200 [00:07<00:00, 26.51it/s]\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Experiment code for different step sizes [graded]\n",
    "step_sizes = [0.01, 0.1, 0.5, 1.0]\n",
    "\n",
    "epsilon = 0.1\n",
    "num_steps = 1000\n",
    "num_runs = 200\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "\n",
    "q_values = {step_size: [] for step_size in step_sizes}\n",
    "true_values = {step_size: None for step_size in step_sizes}\n",
    "best_actions = {step_size: [] for step_size in step_sizes}\n",
    "\n",
    "for step_size in step_sizes:\n",
    "    all_averages = []\n",
    "    for run in tqdm(range(num_runs)):\n",
    "        agent = EpsilonGreedyAgentConstantStepsize\n",
    "        agent_info = {\"num_actions\": 10, \"epsilon\": epsilon, \"step_size\": step_size, \"initial_value\": 0.0}\n",
    "        env_info = {\"random_seed\": run}\n",
    "\n",
    "        rl_glue = RLGlue(env, agent)\n",
    "        rl_glue.rl_init(agent_info, env_info)\n",
    "        rl_glue.rl_start()\n",
    "        \n",
    "        best_arm = np.argmax(rl_glue.environment.arms)\n",
    "\n",
    "        scores = [0]\n",
    "        averages = []\n",
    "        \n",
    "        if run == 0:\n",
    "            true_values[step_size] = np.copy(rl_glue.environment.arms)\n",
    "            \n",
    "        best_action_chosen = []\n",
    "        for i in range(num_steps):\n",
    "            reward, state, action, is_terminal = rl_glue.rl_step()\n",
    "            scores.append(scores[-1] + reward)\n",
    "            averages.append(scores[-1] / (i + 1))\n",
    "            if action == best_arm:\n",
    "                best_action_chosen.append(1)\n",
    "            else:\n",
    "                best_action_chosen.append(0)\n",
    "            if run == 0:\n",
    "                q_values[step_size].append(np.copy(rl_glue.agent.q_values))\n",
    "        best_actions[step_size].append(best_action_chosen)\n",
    "    ax.plot(np.mean(best_actions[step_size], axis=0))\n",
    "    if step_size == 0.01:\n",
    "        np.save(\"step_size\", best_actions[step_size])\n",
    "    \n",
    "ax.plot(np.mean(n_best_actions, axis=0))\n",
    "fig.legend(step_sizes + [\"1/N(A)\"])\n",
    "plt.title(\"% Best Action Taken\")\n",
    "plt.xlabel(\"Steps\")\n",
    "plt.ylabel(\"% Best Action Taken\")\n",
    "vals = ax.get_yticks()\n",
    "ax.set_yticklabels(['{:,.2%}'.format(x) for x in vals])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "4490c3113b9b460e79a0f92ae6fb2433",
     "grade": false,
     "grade_id": "cell-6704fdb6f4f612fb",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Notice first that we are now plotting the amount of time that the best action is taken rather than the average reward. To better  understand the performance of an agent, it can be useful to measure specific behaviors, beyond just how much reward is accumulated. This measure indicates how close the agent’s behaviour is to optimal.\n",
    "\n",
    "It seems as though 1/N(A) performed better than the others, in that it reaches a solution where it takes the best action most frequently. Now why might this be? Why did a step size of 0.5 start out better but end up performing worse? Why did a step size of 0.01 perform so poorly?\n",
    "\n",
    "Let's dig into this further below. Let’s plot how well each agent tracks the true value, where each agent has a different step size method. You do not have to enter any code here, just follow along."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "6c6c60dcf228a25e321b78ea59e86c71",
     "grade": false,
     "grade_id": "cell-49e29a510956e277",
     "locked": true,
     "schema_version": 1,
     "solution": false
    },
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot various step sizes and estimates\n",
    "largest = 0\n",
    "num_steps = 1000\n",
    "for step_size in step_sizes:\n",
    "    plt.figure(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "    largest = np.argmax(true_values[step_size])\n",
    "    plt.plot([true_values[step_size][largest] for _ in range(num_steps)], linestyle=\"--\")\n",
    "    plt.title(\"Step Size: {}\".format(step_size))\n",
    "    plt.plot(np.array(q_values[step_size])[:, largest])\n",
    "    plt.legend([\"True Expected Value\", \"Estimated Value\"])\n",
    "    plt.xlabel(\"Steps\")\n",
    "    plt.ylabel(\"Value\")\n",
    "    plt.show()\n",
    "\n",
    "plt.figure(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "plt.title(\"Step Size: 1/N(A)\")\n",
    "plt.plot([true_values[step_size][largest] for _ in range(num_steps)], linestyle=\"--\")\n",
    "plt.plot(np.array(n_q_values)[:, largest])\n",
    "plt.legend([\"True Expected Value\", \"Estimated Value\"])\n",
    "plt.xlabel(\"Steps\")\n",
    "plt.ylabel(\"Value\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "f0ecb1029a80a609aa9e18b280572f82",
     "grade": false,
     "grade_id": "cell-a0948edb96aacc70",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "These plots help clarify the performance differences between the different step sizes. A step size of 0.01 makes such small updates that the agent’s value estimate of the best action does not get close to the actual value. Step sizes of 0.5 and 1.0 both get close to the true value quickly, but are very susceptible to stochasticity in the rewards. The updates overcorrect too much towards recent rewards, and so oscillate around the true value. This means that on many steps, the action that pulls the best arm may seem worse than it actually is.  A step size of 0.1 updates fairly quickly to the true value, and does not oscillate as widely around the true values as 0.5 and 1.0. This is one of the reasons that 0.1 performs quite well. Finally we see why 1/N(A) performed well. Early on while the step size is still reasonably high it moves quickly to the true expected value, but as it gets pulled more its step size is reduced which makes it less susceptible to the stochasticity of the rewards.\n",
    "\n",
    "Does this mean that 1/N(A) is always the best? When might it not be? One possible setting where it might not be as effective is in non-stationary problems. You learned about non-stationarity in the lessons. Non-stationarity means that the environment may change over time. This could manifest itself as continual change over time of the environment, or a sudden change in the environment.\n",
    "\n",
    "Let's look at how a sudden change in the reward distributions affects a step size like 1/N(A). This time we will run the environment for 2000 steps, and after 1000 steps we will randomly change the expected value of all of the arms. We compare two agents, both using epsilon-greedy with epsilon = 0.1. One uses a constant step size of 0.1, the other a step size of 1/N(A) that reduces over time. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "d04001916905f0fb420618c4014cc638",
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     "grade_id": "cell-55536f4ac923ab96",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 200/200 [00:15<00:00, 13.17it/s]\n",
      "100%|██████████| 200/200 [00:14<00:00, 13.02it/s]\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "epsilon = 0.1\n",
    "num_steps = 2000\n",
    "num_runs = 200\n",
    "step_size = 0.1\n",
    "\n",
    "plt.figure(figsize=(15, 5), dpi= 80, facecolor='w', edgecolor='k')\n",
    "plt.plot([1.55 for _ in range(num_steps)], linestyle=\"--\")\n",
    "\n",
    "for agent in [EpsilonGreedyAgent, EpsilonGreedyAgentConstantStepsize]:\n",
    "    all_averages = []\n",
    "    for run in tqdm(range(num_runs)):\n",
    "        agent_info = {\"num_actions\": 10, \"epsilon\": epsilon, \"step_size\": step_size}\n",
    "        env_info = {\"random_seed\": run}\n",
    "\n",
    "        rl_glue = RLGlue(env, agent)\n",
    "        rl_glue.rl_init(agent_info, env_info)\n",
    "        rl_glue.rl_start()\n",
    "\n",
    "        scores = [0]\n",
    "        averages = []\n",
    "        \n",
    "        for i in range(num_steps):\n",
    "            reward, state, action, is_terminal = rl_glue.rl_step()\n",
    "            scores.append(scores[-1] + reward)\n",
    "            averages.append(scores[-1] / (i + 1))\n",
    "            if i == 1000:\n",
    "                rl_glue.environment.arms = np.random.randn(10)\n",
    "        all_averages.append(averages)\n",
    "        \n",
    "    plt.plot(np.mean(all_averages, axis=0))\n",
    "plt.legend([\"Best Possible\", \"1/N(A)\", \"0.1\"])\n",
    "plt.xlabel(\"Steps\")\n",
    "plt.ylabel(\"Average reward\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "714c6cad23e3d8fe31496ffbe8674620",
     "grade": false,
     "grade_id": "cell-c4a8be88bbcc9b38",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Now the agent with a step size of 1/N(A) performed better at the start but then performed worse when the environment changed! What happened?\n",
    "\n",
    "Think about what the step size would be after 1000 steps. Let's say the best action gets chosen 500 times. That means the step size for that action is 1/500 or 0.002. At each step when we update the value of the action and the value is going to move only 0.002 * the error. That is a very tiny adjustment and it will take a long time for it to get to the true value.\n",
    "\n",
    "The agent with step size 0.1, however, will always update in 1/10th of the direction of the error. This means that on average it will take ten steps for it to update its value to the sample mean.\n",
    "\n",
    "These are the types of tradeoffs we have to think about in reinforcement learning. A larger step size moves us more quickly toward the true value, but can make our estimated values oscillate around the expected value. A step size that reduces over time can converge to close to the expected value, without oscillating. On the other hand, such a decaying stepsize is not able to adapt to changes in the environment. Nonstationarity---and the related concept of partial observability---is a common feature of reinforcement learning problems and when learning online.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 5: Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false,
    "nbgrader": {
     "checksum": "3c335943267e235b3001c228e4bf9ba3",
     "grade": false,
     "grade_id": "cell-3c25a546a3d44e22",
     "locked": true,
     "schema_version": 1,
     "solution": false
    }
   },
   "source": [
    "Great work! You have:\n",
    "- Implemented your first agent\n",
    "- Learned about the effect of epsilon, an exploration parameter, on the performance of an agent\n",
    "- Learned about the effect of step size on the performance of the agent\n",
    "- Learned about a good experiment practice of averaging across multiple runs"
   ]
  },
  {
   "cell_type": "code",
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